Lead Credit Risk Data Scientist

About the role

As a Lead Data Scientist within the Credit Data Science team, you will serve as a domain expert responsible for the end-to-end design, development, and productionization of robust, scalable machine learning solutions for our credit and portfolio management domain. You will own Billie's credit risk modeling domain end-to-end, work in close partnership with Engineering, Product, and Data Science peers, and play a central role in shaping and executing on the roadmap for state-of-the-art ML models and applied AI that power our fast-growing business.

What you'll do

• Take ownership over one of the most important KPIs leading to Billie's success, directly impacting our P&L with your expertise.
• Drive the technical solution and execution of high-quality, impactful ML solutions across multiple domains within the Data Science team, ensuring project success from conception to production.
• Identify and apply advanced AI methodologies to push Billie's credit scoring capabilities beyond conventional approaches, turning emerging techniques into production-ready solutions (e.g. LLMs, RAG, AI agents, foundation models).
• Apply exceptional hands-on expertise in quantitative analysis, data mining, data science, and advanced ML to model complex business patterns, build state-of-the-art credit risk models (PD, LGD, EAD, etc), identify risk factors, and optimize Billie's real-time decision engine logic for various use cases.
• Define and execute the analytics for complex, cross-domain problems, including developing hypotheses for experimentation, designing A/B tests, and synthesizing results into actionable insights.
• Partner closely with Engineering, Product, and Data Science teams to enhance and optimize the decision engine, improving its logic, integrating new data sources, and enhancing functionalities.
• Mentor and grow junior Data Scientists within the team, and bring a technical perspective to system design discussions across backend and ML.

What you'll need

• 6+ years of Data Science experience, with significant exposure to the credit domain and deep expertise in PD modeling: from scorecard development and model validation through to production monitoring.
• Hands-on proficiency in Python (pandas, scikit-learn, XGBoost, PyTorch/TensorFlow) and SQL (Snowflake, BigQuery, etc.), and experience with data visualization tools like Tableau.
• Hands-on experience working with LLMs and generative AI, with the ability to evaluate, integrate, and fine-tune models in a production environment.
• Proven experience leading the deployment and productionization of ML services, demonstrating a deep understanding of modern MLOps concepts like containerization (e.g., Docker, Kubernetes), event-driven architectures, and model monitoring.
• Strong business acumen and the ability to translate complex business problems into clear analytical and technical requirements that deliver maximum value.
• Excellent communication and data storytelling skills, with a track record of maximizing the impact of technical findings on organizational decision-making.
• A strong product mindset: you're comfortable owning a roadmap, making trade-offs under uncertainty, and driving initiatives forward with minimal direction.

Nice to have

• Broader experience with LGD, EAD, limit policies, and portfolio management.
• Hands-on experience with graph databases (e.g., Neo4j) to model, analyze, and extract features from highly interconnected data.

What they offer

• Virtual Shares Incentive Program so everyone at Billie is invested in our success.
• Hybrid working approach allowing up to 3 days per week work from home.
• 30 days vacation per year, sabbatical opportunities, and extra child sickness leave for parents.
• Yearly development budget to broaden your skill set and horizons.
• Discounted access to Berlin Public Transport (BVG), Deutschland-Ticket, or JobRad.
• English-speaking, multicultural team with more than 40 nationalities.